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Preliminary analyses of population attributes (working status, coat colour) did not show associations with hip score, therefore, the genomic relationship matrix was fitted (as explained below) and was assumed to account for any remaining population structure.
Following that, a linear combination of regressors in a design matrix was fitted to the data to produce beta estimates (Friston et al. 1995b), which represent the contribution of a particular regressor to the data.
Also, fitting a pedigree-based relationship matrix (the A matrix) and a genome-based relationship matrix (the G matrix) together can give a higher predictive correlation than when only one matrix was fitted (Crossa et al. 2010).
A design matrix was fitted for each participant, with each type of dance video, as well as button presses, attentional control videos, still-body videos, and fixation modeled as a boxcar function convolved with the standard hemodynamic response function.
A design matrix was fitted for each participant, with each type of dance video (PVA, VA, A, and UNT conditions), as well as button presses, attentional control videos, still body videos modeled together as a boxcar function convolved with the standard hemodynamic response function.
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The design matrix was fit to the data for each participant individually.
In this repeated measures design, a mixed-effects linear model, having an unstructured variance-covariance matrix was fit to each quality of life outcome to assess changes across time (weeks) within and between responder status (responder/non-responder).
Mixed models of substitution, in which a matrix describes the changes among nucleotide pairs and another matrix is fitted for single nucleotide changes, thus potentially provide a better fit to nucleotide sequence data from such molecules [12], [37], [45], [65].
In this approach, a distinction is made between genotyped individuals, including all parents, for which the full relationship matrix is fitted, and non-genotyped non-parent individuals.
Description: The rice dataset is in Table 1 and more details on the traits are available in Additional file 1 Table S1; for all kernels, the first four principal components of the markers design matrix were fitted as fixed effect.
Therefore, GEE models with a logit link and an exchangeable correlation matrix were fitted to produce a population-averaged odds ratio (OR) and a robust estimator to correct the standard errors for the potential correlation of observations within hospitals [ 22].
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